Web Solutions Engineer, Technology and Insights Partnership Systems
Bengaluru, Karnataka, Indiaonsitemidfull timeToday
About the job:
Google's Web Solutions Engineers (WSE) innovate and develop software-based solutions for complex business problems. As an L4 Web Solutions Engineer on the YouTube BizTech team, you are an entrepreneurial full-stack engineer tasked with shaping the future of YouTube’s Business Systems, working with minimal guidance to deliver flawless, scalable solutions.
Responsibilities:
Design, build, and deploy highly scalable AI applications using the Google Cloud AI stack (Vertex AI, Cloud Functions, Agent Development Kits) to solve complex business operations and partner management challenges.
Develop autonomous, multi-agent systems and robust RAG architectures that securely integrate internal knowledge bases and enterprise data silos with large language models, demonstrating an understanding of vector embeddings, context windows, and semantic search.
Seamlessly integrate AI backend services (via APIs and Cloud Functions) with intuitive frontend web applications (using TypeScript/Angular/Lit) to provide insights and automated workflows to end-users.
Develop project plans and deliver AI-focused projects on time, within budget, and in scope with minimal guidance. Identify opportunities where generative AI can eliminate operational friction or technical debt.
Write and review complex Technical Design Documents focused on AI system architecture.
Minimum qualifications:
Bachelor's degree in Computer Science, Electrical Engineering, Math or a related quantitative field, or equivalent practical experience.
4 years of software development and system design, utilizing Python, TypeScript/JavaScript, and SQL.
Experience with front end languages (e.g., JavaScript or TypeScript).
Experience with backend languages (e.g., Java, Python, or C++).
Experience working with database technologies (e.g. SQL, NoSQL).
Preferred qualifications:
4 years of experience designing and optimizing databases.
Experience building and deploying machine learning models, LLM applications, or Generative AI solutions using public cloud infrastructure (e.g., Google Cloud Platform).
Experience writing and reviewing technical documents, including design, development, and revision documents, and performing code reviews in compiled or scripted languages.
Experience building and scaling full-stack web applications and backend API services.
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